AI Era's 'Scarce Assets'? Goldman Sachs: HALO—Heavy Assets, Low Obsolescence

marsbitPublished on 2026-02-25Last updated on 2026-02-25

Abstract

In the AI era, market focus is shifting from scalable, light-asset business models to valuing hard-to-replicate physical assets and infrastructure, a trend Goldman Sachs terms "HALO" (Heavy Assets, Low Obsolescence). This reflects a repricing of scarcity driven by higher real interest rates, geopolitical fragmentation, supply chain restructuring, and massive AI-driven capital expenditure. HALO assets—such as power grids, pipelines, utilities, and critical industrial capacity—have high replication barriers (cost, regulation, engineering complexity) and remain economically durable across technology cycles. Meanwhile, AI is undermining the profitability and terminal value of some light-asset sectors (e.g., software, IT services) by reducing information costs and increasing competition. Notably, major tech firms are now becoming large-scale capital spenders, with projected Capex of $1.5 trillion from 2023-2026—surpassing their cumulative historical investment. Since 2025, Goldman’s heavy-asset portfolio (GSSTCAPI) has outperformed its light-asset counterpart (GSSTCAPL) by 35%, driven by valuation rerating rather than broad de-rating of light assets. Macro factors support this shift: higher rates compress valuations of long-duration growth stocks, while manufacturing and capex cycles benefit heavy-asset firms. Earnings momentum is also stronger for heavy-asset companies, with higher expected CAGR (14% vs. 10%) and improving ROE. Despite recent gains, institutional positioning r...

Author: Trading Desk Insights

As AI products become easier to replicate, the market is beginning to reprice 'hard-to-replicate physical assets' like power grids, pipelines, infrastructure, and long-term production capacity.

On February 24, Goldman Sachs Global Investment Research released a new report titled "The HALO effect: Heavy Assets, Low Obsolescence in the AI era," proposing that under the combined forces of higher real interest rates, geopolitical fragmentation, supply chain restructuring, and the AI capital expenditure wave, the core pricing logic of the stock market is shifting from "scalable, light-asset narratives" to "buildable, hard-to-replace physical capacity and networks."

Goldman Sachs summarizes this change as a "repricing of scarcity."

"Higher real yields, geopolitical fragmentation, and supply chain restructuring are pulling stock leadership back to tangible productive assets. The market is rewarding capacity, networks, infrastructure, and engineering complexity—assets that are costly to replicate and less susceptible to technological disruption."

  • What is HALO?

Goldman Sachs refers to these types of companies as HALO, which stands for the combination of "Heavy Assets" and "Low Obsolescence".

  • Heavy Assets: Business models built on a massive base of physical capital, with high replication barriers—such as cost, regulation, construction time, engineering complexity, or network integration difficulty.

  • Low Obsolescence: The economic relevance of these assets persists through technological cycles.

Typical examples include transmission grids, oil and gas pipelines, utilities, transportation infrastructure, critical equipment, and various industrial capacity categories with replacement cycles that are slow relative to digital innovation.

These assets are difficult to create out of thin air. In today's rapidly evolving digital technology landscape, the replacement cycle for such physical assets is extremely slow. Technological innovation cannot easily replace a transnational oil pipeline, nor can code substitute for a vast national power grid.

Goldman Sachs observes that businesses are decisively returning to physical assets. Capacity, infrastructure, and long-cycle assets are experiencing an unprecedented return to value.

  • Why is the Light-Asset Myth Ending in the AI Era?

Over the past decade, the zero-interest-rate environment and abundant liquidity following the global financial crisis fostered business models centered on scalability rather than physical capital. Tech stocks and light-asset industries enjoyed extremely high valuation premiums.

But this balance has been broken. The rapid rise of artificial intelligence is exerting a powerful "dual pressure" on global stock markets.

First, AI is disrupting the "new economy" model that dominated the past decade, making the "profit margins and terminal value" of some light-asset industries more uncertain. Goldman Sachs states bluntly: "The AI revolution is raising questions about the profit margins and terminal value of software and IT services."

The report names software, IT services, publishing, gaming, logistics platforms, and even the asset management industry, stating that their moats are being reassessed. Goldman's expression is straightforward: "The recent significant devaluation of software and IT services is not due to short-term profit collapse, but rather the market repricing terminal value and margin durability—historically high profitability is now seen as more vulnerable to competitive erosion."

In other words, AI lowers information processing costs but also compresses differentiation, leading the market to score future cash flows more cautiously.

Second, AI is reshaping the landscape of capital expenditure. Goldman Sachs points out: "AI is simultaneously turning some of the most iconic 'light-asset' winners into the biggest capital spenders in history."

To maintain leadership in the foundational large model and computing power race, the five largest US tech giants have embarked on an unprecedented investment cycle. Data shows that since the release of ChatGPT in 2022, these giants' capital expenditure (Capex) from 2023 to 2026 will reach approximately $1.5 trillion. In contrast, they invested only about $600 billion in total throughout their entire history before 2022.

More impactfully, in the single year of 2026 alone, their capital expenditure is expected to exceed $650 billion. This means the investment in just one year will surpass their total historical sum before the AI era. This is the largest and fastest capital expenditure cycle in tech history.

This signifies two things: First, "computing power infrastructure" itself is a typical physical asset cycle; second, AI has not made the world lighter; instead, it has made more industry chains benefit from the ability to "build, supply, and deliver."

When tech giants become "heavy-asset" infrastructure fanatics, the market's faith in the superiority of "light assets" naturally wavers.

The Market is Rewarding HALO with Real Money

Investors'嗅觉 are sharp. The performance difference between Goldman's constructed "Heavy Asset Portfolio" (GSSTCAPI) and "Light Asset Portfolio" (GSSTCAPL) provides the most直观 market answer.

Data shows that asset intensity has become a core driver of valuation and returns. Goldman reveals in the report: "Since 2025, our new Heavy Asset portfolio (GSSTCAPI) has outperformed the Light Asset portfolio (GSSTCAPL) by 35%."

This outperformance is not just relative stock price volatility but a convergence of valuation logic.

In the early 2020s, as the market viewed many old-economy companies as "structural value traps," the valuation of European growth stocks was once more than double that of value stocks, with a premium as high as 150%. But now, the valuation gap between heavy and light assets has narrowed dramatically.

More noteworthy for investors is the manner of this valuation convergence. Goldman points out that their valuations are now almost at the same level, but this convergence is "driven more by the valuation re-rating of heavy-asset companies, rather than a comprehensive valuation downgrade of light-asset companies."

Apart from weakness in some light-asset sectors directly exposed to AI disruption risks like software, the overall market evolution path is: heavy-asset companies actively raised their valuations to meet the level of their light-asset peers. This indicates that market capital is actively paying a premium for the resilience and strategic value of real economic assets.

How to Define "Heavy Assets"? Examining Six Core Metrics

To penetrate traditional industry classifications and accurately identify targets truly reliant on physical capital, Goldman Sachs abandoned single metrics and instead constructed a comprehensive "Capital Intensity Score" system comprising six indicators. This system deeply reflects the new perspective through which the market examines asset quality.

  1. Tangible Asset Intensity (Net Physical Operating Assets / Sales): A higher value means a heavier physical base is required to generate each dollar of revenue.

  2. Fixed Asset Intensity (PP&E / Sales): Reflects the degree of reliance on physical bricks and mortar.

  3. Fixed Asset Share (PP&E / Total Assets): Reveals how much capital on the company's balance sheet is "locked" in long-term physical assets.

  4. Capital-Labor Ratio (Tangible Assets / Number of Employees): Distinguishes whether the business is driven by machinery or by manpower.

  5. Capital Expenditure Intensity (Capex / Sales): Measures the proportion of annual cash flow needed to maintain or expand the business.

  6. Capital Expenditure Burden (Capex / EBITDA): Shows the extent to which operating cash profit is consumed by asset maintenance.

By scanning these six dimensions, Goldman Sachs categorizes companies into distinct camps.

Utilities, basic resources, energy, and telecommunications unsurprisingly firmly occupy the heavy-asset camp. These industries are heavily regulated, have extremely high fixed capital requirements, and very long asset lives.

Conversely, software, IT services, internet, and media platform companies are firmly placed in the light-asset, human-capital-intensive category.

Interestingly, there is a "middle ground" in the market. Goldman found that automobiles and aviation are clearly heavy-asset; but due to brand assets, production process know-how, and long-term investment in craftsmanship, luxury goods and beverages also fall into the "low obsolescence" quality asset category. In contrast, consumer services, gambling, and most retailers are structurally light-asset, with their economic lifeline being labor and marketing, not physical capital.

Resonance of Macro Tailwinds and Earnings Momentum

Why are heavy assets booming at this particular juncture? The answer lies in the dual resonance of macroeconomic indicators and corporate fundamentals.

On the interest rate front, heavy-asset stocks often perform well during periods of higher interest rates. Because high yields relentlessly compress the valuations of long-duration, light-asset growth companies. Conversely, heavy-asset sectors tied to tangible capacity can benefit from stronger nominal economic activity and government fiscal spending. Goldman mentions that the current policy mix is guiding capital towards physical assets, "creating a structural tailwind for capital-intensive companies."

On the macro cycle front, the博弈 between manufacturing and services is a key风向标. The fate of heavy-asset sectors is closely linked to industrial production and capital expenditure cycles. Goldman observes that as the Manufacturing PMI (especially the future business expectations component) recovers and surpasses the Services PMI, the macro backdrop is tilting back in favor of heavy-asset industries.

And on the earnings front, which determines the long-term performance of the stock market, the fundamental balance has also tilted.

In the past cycle, light-asset companies enjoyed long-term valuation premiums due to consistently high profit growth. But entering 2025, although heavy-asset companies' short-term profits were impacted by disturbances like tariffs (as commodity producers and export-oriented companies, they are far more affected by tariffs than service industries), the trend is clear after stripping away short-term noise.

Goldman emphasizes: "The earnings momentum of heavy-asset companies has recently turned positive, with consensus expectations being revised upwards; while the earnings expectations of light-asset companies are being revised downwards."

Looking forward, analyst consensus expects the EPS compound annual growth rate (CAGR) for the heavy-asset portfolio to reach 14% in the coming years, compared to only 10% for the light-asset portfolio. More critically, the core metric that long supported the high valuation of light assets—Return on Equity (ROE)—is showing signs of fatigue. The market currently expects the ROE of light-asset companies to remain flat, while the ROE of heavy-asset companies is expected to continue improving.

Fund Crowding: The Rotation to Heavy Assets Has Just Begun

Since the logic is so clear and valuations have converged, has this wave of heavy-asset行情 run its course?

From the perspective of fund博弈, it is far from over.

The recent outperformance of heavy assets is closely related to the market's extreme desire to escape crowded and expensive "US tech stock" positions. Over the past 12 months, European value funds have seen a net inflow of 3%, while growth funds have experienced a net outflow of 9%.

But Goldman Sachs pointedly notes that despite the intense short-term rotation, long-term fund positioning remains very weak: "The cumulative net outflow of European value funds relative to growth funds still hovers around -40% of Assets Under Management."

This means global investors remain severely underweight value stocks (the concentration of heavy assets). Based on this huge position gap, the structural logic for heavy-asset stocks to continue outperforming light-asset stocks remains rock solid.

In this era being rapidly reshaped by AI, the frenetic advance of the virtual world is instead making the steel, pipelines, and power grids of the physical world unprecedentedly precious. Whether this is a lasting change in market leadership or a rebalancing within the cycle, for investors, the "bulletproof"属性 of physical capital is radiating an undeniable glow.

Related Questions

QWhat does HALO stand for in the context of Goldman Sachs' report, and what are its two core components?

AHALO stands for 'Heavy Assets, Low Obsolescence'. Its two core components are: 1) Heavy Assets: Business models built on a massive base of physical capital with high replication barriers (e.g., cost, regulation, construction time, engineering complexity). 2) Low Obsolescence: The economic relevance of these assets persists through technology cycles.

QAccording to Goldman Sachs, what are the two main ways AI is exerting a 'dual pressure' on the global equity market?

A1) AI is disrupting the 'new economy' model by making the future profitability and terminal value of some light-asset industries (like software, IT services) more uncertain, as it lowers information processing costs and compresses differentiation. 2) AI is reshaping the capital expenditure landscape, turning iconic 'light-asset' winners into some of the largest capital spenders in history to compete in the AI arms race.

QWhat was the performance difference between Goldman's heavy-asset portfolio (GSSTCAPI) and its light-asset portfolio (GSSTCAPL) since 2025?

ASince 2025, Goldman Sachs' new heavy-asset portfolio (GSSTCAPI) has outperformed its light-asset portfolio (GSSTCAPL) by 35%.

QName at least four of the six metrics Goldman Sachs employs to define a company's 'capital intensity score'.

AFour of the six metrics are: 1) Tangible asset intensity (net physical operating assets/sales), 2) Fixed asset intensity (PP&E/sales), 3) Fixed asset share (PP&E/total assets), 4) Capital-labor ratio (tangible assets/employee), 5) Capex intensity (Capex/sales), 6) Capex burden (Capex/EBITDA).

QWhy does Goldman Sachs believe the rotation into heavy-asset stocks is far from over, based on fund positioning?

ABecause long-term fund positioning remains very weak. Despite recent inflows, European value funds (where heavy-asset stocks are concentrated) still show cumulative net outflows of around -40% of assets under management relative to growth funds, indicating global investors remain severely underweight these assets and creating room for further outperformance.

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